The Temporal Dynamics of Learning

沿着其学术和企业合作伙伴，加州大学圣地亚哥分校将建立一个多学科中心，研究学习的时间动态，动态学习中心，涉及来自认知科学，机器学习和机器人技术，发展和感知心理学，神经科学等领域的研究人员。该中心的行政办公地点将设在圣地亚哥的加州大学，合作机构包括罗格斯大学和范德比尔特大学，并有加州大学伯克利分校、布朗大学、卡内基梅隆大学、科罗拉多大学博尔德分校、匹兹堡大学、昆士兰州、圣地亚哥州立大学索尔克研究所、维多利亚、该中心的智力价值将是其重点放在学习中的时间和时机的作用，在多个时间尺度和多个系统。很明显，这些层次的描述不能孤立地理解，或者只从一个学科的方法。 该团队建议整合机器学习，社会机器人，学习和记忆的神经生物学，电生理学，脑成像，行为和理论神经科学的工作，以开发一个新的，综合的多时间尺度学习动态的观点。该中心将是独特的，其重点是研究网络组成的跨学科科学家团队解决共同的问题，在学习的时间和时间的研究。这项建议的更广泛的影响将是：第一，开发新的培训活动和网络基础设施，以使真正的跨学科合作研究成为可能;第二，与当地学校合作开展新的教育活动;第三，开发新的公共宣传计划。 与典型的培训计划不同，培训活动将针对高级科学家以及学生和初级科学家;它们将涉及一系列工具，包括密集的“训练营”，实习和暑期学校。中心科学家和选择课堂教师将相互教育，以实现科学的有效翻译相关的课堂举措。翻译到课堂将由该中心的教育技术合作伙伴的专业知识促进。该中心将招募新的本科生和研究生，通过与罗格斯大学纽瓦克分校和加州大学圣地亚哥分校的低收入学生特许学校，普劳斯学校的合作伙伴关系，增加学生人口的广度和多样性的特定目标。该中心将为高中生提供实习机会;每年夏天为大约80名市中心高中生举办“实现明天”项目的强化讲习班，并为教师举办夏季讲习班。该中心的研究将通过科学网络向公众传播，这是一个基于网络的多媒体节目平台，将成为那些关注科学及其对社会影响的人的可信目的地。该中心的模式对这项事业至关重要，因为它的雄心勃勃的目标是创造一门关于学习时间动态的新科学。在这一学科中解决基本问题将需要大量致力于科学家和教师的技术支持，以孵化想法，共享数据，共享研究工具和理论进步。数据共享设施，将使这种互动将成为一个模型技术和软件架构，为未来的合作科学。

Along with its academic and corporate partners, UCSD will establish a multidisciplinary Center to study the temporal dynamics of learning, the Dynamic Learning Center, involving investigators from fields as diverse as cognitive science, machine learning and robotics, developmental and perceptual psychology, and neuroscience. The administrative location of the Center will be at the University of California, San Diego, with partner institutions, Rutgers University and Vanderbilt University and substantive participation from investigators at UC Berkeley, Brown, CMU, CU Boulder, Pittsburgh, Queensland, the Salk Institute, San Diego State University, Victoria, and Yale.The intellectual merit of the Center will be its focus upon the role of time and timing in learning, at multiple time scales and in multiple systems. It is clear that these levels of description cannot be understood in isolation, or from only one disciplinary approach. The team proposes to integrate work in machine learning, social robotics, the neurobiology of learning and memory, electrophysiology, brain imaging, behavior, and theoretical neuroscience in order to develop a new, integrated view of the dynamics of learning at multiple time scales. The Center will be unique in its emphasis on research networks composed of interdisciplinary teams of scientists addressing common questions in the study of time and timing in learning. The broader impact of this proposal will be first, to develop novel training activities and cyberinfrastructure in order to make truly collaborative interdisciplinary research possible; second, to work with local schools on novel educational initiatives; and third, to develop new public outreach programs. Unlike typical training programs, the training activities will be aimed at senior scientists as well as students and junior scientists; and they will involve a range of vehicles, including intensive "bootcamps," internships, and summer schools. Center scientists and select classroom teachers will educate each other in order to achieve effective translation of the science to pertinent classroom initiatives. Translation to the classroom will be facilitated by the expertise of the Center's corporate partners in educational technology. The Center will recruit new undergraduate and graduate students, with the particular goal of increasing the breadth and diversity of the student population, through partnerships with Rutgers Newark and UCSD's charter school for low-income students, The Preuss School. The Center will provide internships for high school students; intensive workshops for approximately 80 inner-city high school students in the Reach for Tomorrow program each summer, and a summer workshop for teachers. The Center's research will be disseminated to the public through the medium of The Science Network, a web-based multi-media programming platform that will be a trusted destination for those concerned with science and its impact on society.The center mode is essential to this enterprise, given the ambitious goal of creating a new science of the temporal dynamics of learning. Answering fundamental questions in this discipline will require technological support for a large group of committed scientists and teachers to incubate ideas, share data, share research tools, and theoretical advances. The Data Sharing Facility that will enable this interaction will become a model technology and software architecture for future collaborative science.